Feature validation

Learn whether a feature solves the right problem before you build it.

Askli interviews people with relevant experience, examines their existing workflow, and shows what would make the feature useful, trustworthy, or unnecessary.

Validate a Feature See the methodology

Evidence for prioritization

Test the need, the workflow, and the conditions for adoption.

Problem experience

Confirm whether the proposed problem occurs, who experiences it, and when it becomes costly enough to matter.

Current workflow

Learn how people complete the task today, including workarounds and alternatives your feature must displace.

Feature relevance

Explore which part of the proposal connects to the need and which details add complexity without value.

Adoption concerns

Surface trust, control, compatibility, learning effort, and other conditions that could prevent real use.

Illustrative research objectives

A feature question becomes an investigation of behavior and tradeoffs.

Illustrative Askli outputExample only — not results from a real study
Research question

Would people who track expenses regularly trust automatic expense categorization, and what would make them adopt it?

Research objectives
  • Understand how people categorize and correct expenses today
  • Identify where the existing workflow consumes time or creates errors
  • Learn the control and transparency required before automation feels trustworthy
Example adaptive follow-up

“Think about the last incorrect category you found. How did you notice it, and what did you do?”

Possible supporting evidence

Illustrative: a participant may value automation when corrections are visible, reversible, and remembered.

Possible contradictory evidence

Illustrative: a participant may prefer manual control because errors affect budgeting decisions and tax records.

Decision implication

Test a correction-first interaction and evidence of learned preferences before prioritizing full automation.

A better roadmap question

Move from “Do users like it?” to “What evidence would justify priority?”

Feature requests and positive reactions can hide different underlying needs. Askli probes recent examples, alternatives, expected value, and adoption barriers so the team can distinguish a strong signal from a polite response.

See how findings stay linked to evidence

Feature validation FAQ

Use customer evidence without treating every request as a roadmap commitment.

What should feature validation investigate?

Start with the underlying problem, current workflow, expected value, adoption conditions, and reasons the feature may be unnecessary—not only whether people say they like it.

Can I validate a feature before I have a prototype?

Yes. Early interviews can test the problem and expected value. A concrete design or prototype is more appropriate when the decision depends on comprehension or usability.

Does positive feedback mean I should build the feature?

Not by itself. Askli preserves the context, counter-evidence, uncertainty, and behavior behind reactions so the team can judge whether the evidence supports prioritization.

Before engineering starts

Test whether the feature earns its place.

Start a focused Quick Check and review the proposed audience and objective before checkout.

Validate a Feature